On Reciprocal Causation in the Evolutionary Process

Recent calls for a revision of standard evolutionary theory (SET) are based partly on arguments about the reciprocal causation. Reciprocal causation means that cause–effect relationships are bi-directional, as a cause could later become an effect and vice versa. Such dynamic cause-effect relationships raise questions about the distinction between proximate and ultimate causes, as originally formulated by Ernst Mayr. They have also motivated some biologists and philosophers to argue for an Extended Evolutionary Synthesis (EES). The EES will supposedly expand the scope of the Modern Synthesis (MS) and SET, which has been characterized as gene-centred, relying primarily on natural selection and largely neglecting reciprocal causation. Here, I critically examine these claims, with a special focus on the last conjecture. I conclude that reciprocal causation has long been recognized as important by naturalists, ecologists and evolutionary biologists working in the in the MS tradition, although it it could be explored even further. Numerous empirical examples of reciprocal causation in the form of positive and negative feedback are now well known from both natural and laboratory systems. Reciprocal causation have also been explicitly incorporated in mathematical models of coevolutionary arms races, frequency-dependent selection, eco-evolutionary dynamics and sexual selection. Such dynamic feedback were already recognized by Richard Levins and Richard Lewontin in their bok The Dialectical Biologist. Reciprocal causation and dynamic feedback might also be one of the few contributions of dialectical thinking and Marxist philosophy in evolutionary theory. I discuss some promising empirical and analytical tools to study reciprocal causation and the implications for the EES. Finally, I briefly discuss how quantitative genetics can be adapated to studies of reciprocal causation, constructive inheritance and phenotypic plasticity and suggest that the flexibility of this approach might have been underestimated by critics of contemporary evolutionary biology.     

"Are we there yet?": Deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits

Although mathematical relationships can be proven by deductive logic, biological relationships can only be inferred from empirical observations. This is a distinct disadvantage for those of us who strive to identify the genes involved in complex diseases and quantitative traits. If causation cannot be proven, however, what does constitute sufficient evidence for causation? The philosopher Karl Popper said, "Our belief in a hypothesis can have no stronger basis than our repeated unsuccessful critical attempts to refute it." We believe that to establish causation, as scientists, we must make a serious attempt to refute our own hypotheses and to eliminate all known sources of bias before association becomes causation. In addition, we suggest that investigators must provide sufficient data and evidence of their unsuccessful efforts to find any confounding biases. In this editorial, we discuss what "causation" means in the context of complex diseases and quantitative traits, and we suggest guidelines for steps that may be taken to address possible confounders of association before polymorphisms may be called "causative."     

Making sense of downward causation in manipulationism: illustrations from cancer research

Many researchers consider cancer to have molecular causes, namely mutated genes that result in abnormal cell proliferation (e.g. Weinberg 1998). For others, the causes of cancer are to be found not at the molecular level but at the tissue level where carcinogenesis consists of disrupted tissue organization with downward causation effects on cells and cellular components (e.g. Sonnenschein and Soto 2008). In this contribution, I ponder how to make sense of such downward causation claims. Adopting a manipulationist account of causation (Woodward 2003), I propose a formal definition of downward causation and discuss further requirements (in light of Baumgartner 2009). I then show that such an account cannot be mobilized in support of non-reductive physicalism (contrary to Raatikainen 2010). However, I also argue that such downward causation claims might point at particularly interesting dynamic properties of causal relationships that might prove salient in characterizing causal relationships (following Woodward 2010).     

Genes,germs, and schizophrenia: an evolutionary perspective

Literature on schizophrenia and other mental illnesses has emphasized the compatibility of evidence with genetic causation without adequately considering alternative hypotheses of disease causation. Although some studies from the mid-20th century reported associations between certain pathogens and schizophrenia, only recently has the possibility of infectious causation of schizophrenia again become an active focus of research. Infectious causation of schizophrenia is still, however, generally regarded as less well demonstrated than genetic causation. This article evaluates the evidence that has been used to support genetic and infectious causation. Our consideration of infectious causation focuses on the protozoan Toxoplasma gondii but also assesses other pathogens that may contribute to the development of some of the illnesses currently categorized as schizophrenia. Although evidence generally accepted as demonstrating genetic causation can be readily explained by hypotheses of infectious causation, some of the evidence implicating infectious causation cannot be similarly explained by genetic causation. This asymmetry indicates that a scientific approach to the causation of schizophrenia needs to put a greater emphasis on tests that distinguish hypotheses of genetic causation from those of infectious causation.     

Reciprocal causation and the proximate–ultimate distinction

Laland and colleagues have sought to challenge the proximate–ultimate distinction claiming that it imposes a unidirectional model of causation, is limited in its capacity to account for complex biological phenomena, and hinders progress in biology. In this article the core of their argument is critically analyzed. It is claimed that contrary to their claims Laland et al. rely upon the proximate–ultimate distinction to make their points and that their alternative conception of reciprocal causation refers to phenomena that were already accounted for by standard theory.     

Ecological correlates of secondary sexual dimorphism in Salix glauca (Salicaceae)

The ecological causation hypothesis for secondary sexual dimorphism was tested in Salix glauca, a dioecious willow shrub. Plants growing in a Colorado Rocky Mountain (USA) krummholz mosaic of mesic and xeric patches were monitored for four consecutive years. Ecological causation is predicated on unique resource demands associated with sexual function. In S. glauca, seeds have twofold higher N and P concentrations compared to pollen. P, but not N, allocation costs differed between sexes at plant and flower scales. Ecological causation also predicts spatial segregation of sexes along underlying habitat gradients. In five populations of S. glauca, sexes displayed significant spatial segregation. The theory also predicts that sexes differ in performance across gradients of environmental stress or resource availability. Consistent with this hypothesis, females had lower drought tolerance than males under years of extreme aridity. Furthermore, over 10 years, annual shoot growth for females was greatest in mesic habitat patches, while males grew at a consistent rate regardless of habitat aridity. Because current shoot growth is correlated with future catkin production, habitat specialization likely provides a fitness payoff in females. Overall, this long-term study provides some of the strongest evidence to date for ecological causation of secondary sexual dimorphism in plants.     

Anorexia nervosa

Anorexia nervosa remains an enigma among Western cultures. Various causal explanations have been offered, encompassing biological, psychological, and sociocultural models. These explanations, however, focus on the immediate or proximal mechanisms of causation. A more thorough understanding of anorexia nervosa can be achieved by understanding the relationship between these factors and ultimate causation, the level of explanation which deals with individual reproductive fitness. This paper reviews the biological, psychological, sociocultural, and evolutionary models and indicates a necessary synthesis between proximate and ultimate levels of causation in examining the anorexia nervosa puzzle.     

Causation and space-time

This paper considers the physical accounts of causation in terms of conserved quantities in the light of the theory of general relativity. As it is rather well-known among physicists, there are several difficulties with the notions of conservation and localization of the (gravitational) energy-momentum within general relativity. We first begin to review the so-called conserved quantity theory of causation mainly due to Dowe and Salmon, then we discuss some consequences of these difficulties for this physical account of causation. We argue that these difficulties are due to the fundamental nature of the space-time structure as described by GR, which the conserved quantity theory of causation does not account for.     

The probability of causation under a stochastic model for individual risk

In this paper we offer a mathematical definition for the probability of causation that formalizes the legal and ordinary-language meaning of the term. We show that, under this definition, even the average probability of causation among exposed cases is not identifiable from epidemiologic data. This is because the probability of causation depends both on the unknown mechanisms by which exposure affects disease risk and competing risks, and on the unknown degree of heterogeneity in the background disease risk of the exposed population. We derive the maximum and minimum values for the probability of causation consistent with the observable population quantities. We also derive the relationship of the "assigned share" (excess incidence rate as a proportion of total incidence rate) to the probability of causation.     

Etiology in psychiatry: embracing the reality of poly‐gene‐environmental causation of mental illness

Intriguing findings on genetic and environmental causation suggest a need to reframe the etiology of mental disorders. Molecular genetics shows that thousands of common and rare genetic variants contribute to mental illness. Epidemiological studies have identified dozens of environmental exposures that are associated with psychopathology. The effect of environment is likely conditional on genetic factors, resulting in gene‐environment interactions. The impact of environmental factors also depends on previous exposures, resulting in environment‐environment interactions. Most known genetic and environmental factors are shared across multiple mental disorders. Schizophrenia, bipolar disorder and major depressive disorder, in particular, are closely causally linked. Synthesis of findings from twin studies, molecular genetics and epidemiological research suggests that joint consideration of multiple genetic and environmental factors has much greater explanatory power than separate studies of genetic or environmental causation. Multi‐factorial gene‐environment interactions are likely to be a generic mechanism involved in the majority of cases of mental illness, which is only partially tapped by existing gene‐environment studies. Future research may cut across psychiatric disorders and address poly‐causation by considering multiple genetic and environmental measures across the life course with a specific focus on the first two decades of life. Integrative analyses of poly‐causation including gene‐environment and environment‐environment interactions can realize the potential for discovering causal types and mechanisms that are likely to generate new preventive and therapeutic tools.     

A computable expression of closure to efficient causation

In this paper, we propose a mathematical expression of closure to efficient causation in terms of λ-calculus; we argue that this opens up the perspective of developing principled computer simulations of systems closed to efficient causation in an appropriate programming language. An important implication of our formulation is that, by exhibiting an expression in λ-calculus, which is a paradigmatic formalism for computability and programming, we show that there are no conceptual or principled problems in realizing a computer simulation or model of closure to efficient causation. We conclude with a brief discussion of the question whether closure to efficient causation captures all relevant properties of living systems. We suggest that it might not be the case, and that more complex definitions could indeed create crucial some obstacles to computability.     

On physicalism and Downward Causation in Developmental and Cancer Biology

The dominant position in Philosophy of Science contends that downward causation is an illusion. Instead, we argue that downward causation doesn't introduce vicious circles either in physics or in biology. We also question the metaphysical claim that "physical facts fix all the facts." Downward causation does not imply any contradiction if we reject the assumption of the completeness and the causal closure of the physical world that this assertion contains. We provide an argument for rejecting this assumption. Furthermore, this allows us to reconsider the concept of diachronic emergence.     

Electromagnetic-field exposure and cancer

Electromagnetic fields are a ubiquitous part of man's environment. Natural sources of energy have been present, and possibly have contributed to the processes of the evolution of living forms. In very recent time, however, exploitation of the properties of the electromagnetic spectrum, has added variables in intensity, frequency, modulation frequency, and alterations in contributions of electrical and magnetic components. Biological impact has been little studied and poorly defined. Animal carcinogenesis studies and human epidemiological data indicate that exposure to nonionizing radiation can play a role in cancer causation. Numerous effects at the physiological and biochemical level have been reported; many are of such a nature that a relationship to the causation of neoplastic transformation can rationally be hypothesized. Many bioeffects of electromagnetic fields can be adequately and economically explained in terms of heat effects alone. However, observations of frequency-, pulse form or modulation-, and intensity-specificity as well as effects opposite to that known for temperature-rise, imply direct interaction of radiant energy with biomolecules. The possibility of such direct interaction has been shown in quantum mechanical models.     

The cement of medical thought. Evolutionary emergence and downward causation.

The aetio-pathogenetic sequences and the physio-pathological patterns of diabetes, emphysema, cholera, circulatory shock and thrombosis have been analysed with respect to an evolutionary interpretation. The diseases, although reflecting alterations of processes that can always be described in physico-chemical language, occur only at the level of biological systems which reflects the decodification of genomic project: the teleonomic projects that have been developed during evolution. The concepts of evolutionary emergence and of downward causation have been used to discuss the relationship between the molecular events responsible for the initiation of the disease, and the subsequent events responsible for the aetio-pathogenesis, for the systemic disarrangement and for the additional alterations of tissues and cells independent of the initial molecular events. In diabetes the systemic disarrangement, glycosuria and hyperglycemia, reflect the evolutionary emergence of the processes regulating carbohydrate metabolism, whereas the cardiovascular and neurological alterations are effects of the systemic disarrangement by a mechanism of downward causation. The complexity of the aetio-pathogenesis and of the physio-pathological patterns of diseases is due to the generation of information during the evolution of multi-hierarchical entities. The evolutionary epistemology approach is useful to explain the behaviour of complex systems.     

Shipley, B. Cause and correlation in Biology

As indicated by the title, this book seeks to address the relationshipbetween correlation and causation, with application to biologicaltopics. The book begins with a statement of three objectives:(1) to persuade biologists that it is possible to infer causationwith observational (non-experimental) data; (2) to describecertain methods that can assist in this process; and (3) toillustrate the methods presented using biological examples. A philosophical discussion of causation is potentially confusingand can often evoke debate, which necessitates some carefullycrafted effort at the beginning of the book to address the meaningof causation. Fortunately for all involved, the methods presenteddo not depend on any one particular definition     

Causal Characteristics for Ecoepidemiology

We suggest that there are six fundamental characteristics of causation: time order, co-occurrence, preceding causation, sufficiency, interaction, and alteration. The cause precedes the effect (time order). The cause co-occurs with the unaffected entity in space and time (co-occurrence). Causes and their effects are the result of a web of causation (preceding causation). The intensity, frequency, and duration of the cause are adequate and the susceptible entity can exhibit the type and magnitude of the effect (sufficiency). The cause effectively interacts with the entity in a way that induces the effect (interaction). And, the entity is changed by the interactions with the cause (alteration). In contrast to Hill's criteria, the causal characteristics are distinct from the: (1) evidence that is used to document causal characteristics, (2) sources of information used to develop the evidence, and (3) qualities used to evaluate evidence of causal characteristics and body of evidence for the causal relationship. Evidence of causal characteristics can form the basis for assessments of epidemiological studies and can structure an explanatory narrative that is causally relevant and substantive. Six core characteristics may be easier to organize, evaluate, communicate, and for decision-makers to assimilate, remember, and inspire action.     

Collaboration,not co-optation.

Studies of health effects of urea formaldehyde foam insulation (UFFI) were critically reviewed by means of accepted rules for evidence of causation. Three categories of health effects were examined: reported symptoms, primarily of the upper respiratory tract, lower respiratory tract disease and cancer. Most of the studies purporting to demonstrate health effects of UFFI failed to meet minimal methodologic criteria for evidence of causation. Evidence from the adequate studies provides little support for the hypothesis of a causative role of UFFI in health problems.     

Rethinking Causation for Data-intensive Biology: Constraints,Cancellations, and Quantized Organisms

Complex organisms thwart the simple rectilinear causality paradigm of “necessary and sufficient,” with its experimental strategy of “knock down and overexpress.” This Essay organizes the eccentricities of biology into four categories that call for new mathematical approaches; recaps for the biologist the philosopher's recent refinements to the causation concept and the mathematician's computational tools that handle some but not all of the biological eccentricities; and describes overlooked insights that make causal properties of physical hierarchies such as emergence and downward causation straightforward. Reviewing and extrapolating from similar situations in physics, it is suggested that new mathematical tools for causation analysis incorporating feedback, signal cancellation, nonlinear dependencies, physical hierarchies, and fixed constraints rather than instigative changes will reveal unconventional biological behaviors. These include “eigenisms,” organisms that are limited to quantized states; trajectories that steer a system such as an evolving species toward optimal states; and medical control via distributed “sheets” rather than single control points.     

Causation in the sciences: An inferentialist account

I present an alternative account of causation in the biomedical and social sciences according to which the meaning of causal claims is given by their inferential relations to other claims. Specifically, I will argue that causal claims are (typically) inferentially related to certain evidential claims as well as claims about explanation, prediction, intervention and responsibility. I explain in some detail what it means for a claim to be inferentially related to another and finally derive some implication of the proposed account for the epistemology, semantics and metaphysics of causation.     

Counterfactual overdetermination vs. the causal exclusion problem

This paper aims to show that a counterfactual approach to causation is not sufficient to provide a solution to the causal exclusion problem in the form of systematic overdetermination. Taking into account the truthmakers of causal counterfactuals provides a strong argument in favour of the identity of causes in situations of translevel, causation.